Integrating imperfect production, screening errors, item deterioration, rising transportation costs, and carbon emissions for sustainable optimization

In today's globalized economy, supply chain efficiency is crucial, particularly when it comes to managing production and distribution in systems with complex product characteristics, such as deterioration and defects. While various studies have addressed characteristics like product deterioration, and defects in supply chains, there is limited research on integrating all these factors under a sustainable framework. The few models that do exist often neglect the real-world complexity of dynamic transportation costs, carbon emissions, and inspection errors. Global economic instability, fluctuating fuel prices, and logistic challenges contribute to continually increasing transportation costs. They can significantly impact the profitability of supply chain operations, particularly for companies relying on long-haul delivery or rapid delivery models. Optimization models that ignore the dynamic nature of transportation costs fail to provide robust solutions in the long term. Moreover, the existing literature often overlooks the combined impact of exponential production and demand rates, and inspection errors on perishable and defective items. Real world businesses face mounting pressure to not only optimize costs but also to address sustainability and environmental concerns. Incorporating carbon emissions from transportation emphasizes the environmental impact of supply chain operations, thereby aligning the model with the current concerns about sustainability and social responsibility. By integrating these factors, the proposed model offers a more comprehensive framework in analyzing supply chain operations for an improved decision-making. The developed model is further assessed through numerical examples for its practical applicability and validation. The findings offer valuable insights for supply chain managers, thereby emphasizing the importance of integrating production characteristics, inspection accuracy, and sustainability into decision-making processes.